Arbeitspapier
Variable selection and inference for multi-period forecasting problems
This paper conducts a broad-based comparison of iterated and direct multi-step forecasting approaches applied to both univariate and multivariate models. Theoretical results and Monte Carlo simulations suggest that iterated forecasts dominate direct forecasts when estimation error is a first-order concern, i.e. in small samples and for long forecast horizons. Conversely, direct forecasts may dominate in the presence of dynamic model misspecification. Empirical analysis of the set of 170 variables studied by Marcellino, Stock and Watson (2006) shows that multivariate information, introduced through a parsimonious factor-augmented vector autoregression approach, improves forecasting performance for many variables, particularly at short horizons.
- Sprache
-
Englisch
- Erschienen in
-
Series: CESifo Working Paper ; No. 2543
- Klassifikation
-
Wirtschaft
- Thema
-
Zeitreihenanalyse
Prognoseverfahren
Autokorrelation
Faktorenanalyse
Multivariate Analyse
Monte-Carlo-Methode
Theorie
Schätzung
Konjunktur
USA
- Ereignis
-
Geistige Schöpfung
- (wer)
-
Pesaran, Mohammad Hashem
Pick, Andreas
Timmermann, Allan
- Ereignis
-
Veröffentlichung
- (wer)
-
Center for Economic Studies and ifo Institute (CESifo)
- (wo)
-
Munich
- (wann)
-
2009
- Handle
- Letzte Aktualisierung
-
10.03.2025, 11:43 MEZ
Datenpartner
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. Bei Fragen zum Objekt wenden Sie sich bitte an den Datenpartner.
Objekttyp
- Arbeitspapier
Beteiligte
- Pesaran, Mohammad Hashem
- Pick, Andreas
- Timmermann, Allan
- Center for Economic Studies and ifo Institute (CESifo)
Entstanden
- 2009
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